C# Class FannWrapperDouble.neural_net

Inheritance: global::System.IDisposable

Exibir arquivo Open project: joelself/FannCSharp Class Usage Examples

Protected Properties

Property	Type	Description
swigCMemOwn	bool

Public Methods

Method	Description
Dispose ( ) : void
cascadetrain_on_data ( training_data data, uint max_neurons, uint neurons_between_reports, float desired_error ) : void
cascadetrain_on_file ( string filename, uint max_neurons, uint neurons_between_reports, float desired_error ) : void
clear_scaling_params ( ) : bool
copy_from_struct_fann ( SWIGTYPE_p_fann other ) : void
create_from_file ( string configuration_file ) : bool
create_shortcut ( uint num_layers ) : bool
create_shortcut_array ( uint num_layers, SWIGTYPE_p_unsigned_int layers ) : bool
create_sparse ( float connection_rate, uint num_layers ) : bool
create_sparse_array ( float connection_rate, uint num_layers, SWIGTYPE_p_unsigned_int layers ) : bool
create_standard ( uint num_layers ) : bool
create_standard_array ( uint num_layers, SWIGTYPE_p_unsigned_int layers ) : bool
descale_input_ ( double descale_vector ) : void
descale_output_ ( double descale_vector ) : void
descale_train ( training_data data ) : void
destroy ( ) : void
disable_seed_rand ( ) : void
enable_seed_rand ( ) : void
get_MSE ( ) : float
get_activation_function ( int layer, int neuron ) : ActivationFunction
get_activation_steepness ( int layer, int neuron ) : double
get_bias_array ( SWIGTYPE_p_unsigned_int bias ) : void
get_bit_fail ( ) : uint
get_bit_fail_limit ( ) : double
get_cascade_activation_functions ( ) : SWIGTYPE_p_FANN__activation_function_enum
get_cascade_activation_functions_count ( ) : uint
get_cascade_activation_steepnesses ( ) : SWIGTYPE_p_double
get_cascade_activation_steepnesses_count ( ) : uint
get_cascade_candidate_change_fraction ( ) : float
get_cascade_candidate_limit ( ) : double
get_cascade_candidate_stagnation_epochs ( ) : uint
get_cascade_max_cand_epochs ( ) : uint
get_cascade_max_out_epochs ( ) : uint
get_cascade_num_candidate_groups ( ) : uint
get_cascade_num_candidates ( ) : uint
get_cascade_output_change_fraction ( ) : float
get_cascade_output_stagnation_epochs ( ) : uint
get_cascade_weight_multiplier ( ) : double
get_connection_array ( Connection connections ) : void
get_connection_rate ( ) : float
get_errno ( ) : uint
get_errstr ( ) : string
get_layer_array ( SWIGTYPE_p_unsigned_int layers ) : void
get_learning_momentum ( ) : float
get_learning_rate ( ) : float
get_network_type ( ) : NetworkType
get_num_input ( ) : uint
get_num_layers ( ) : uint
get_num_output ( ) : uint
get_quickprop_decay ( ) : float
get_quickprop_mu ( ) : float
get_rprop_decrease_factor ( ) : float
get_rprop_delta_max ( ) : float
get_rprop_delta_min ( ) : float
get_rprop_delta_zero ( ) : float
get_rprop_increase_factor ( ) : float
get_sarprop_step_error_shift ( ) : float
get_sarprop_step_error_threshold_factor ( ) : float
get_sarprop_temperature ( ) : float
get_sarprop_weight_decay_shift ( ) : float
get_total_connections ( ) : uint
get_total_neurons ( ) : uint
get_train_error_function ( ) : ErrorFunction
get_train_stop_function ( ) : StopFunction
get_training_algorithm ( ) : TrainingAlgorithm
init_weights ( training_data data ) : void
neural_net ( ) : FANNCSharp
neural_net ( NetworkType net_type, uint num_layers ) : FANNCSharp
neural_net ( NetworkType net_type, uint num_layers, SWIGTYPE_p_unsigned_int layers ) : FANNCSharp
neural_net ( SWIGTYPE_p_fann other ) : FANNCSharp
neural_net ( float connection_rate, uint num_layers ) : FANNCSharp
neural_net ( float connection_rate, uint num_layers, SWIGTYPE_p_unsigned_int layers ) : FANNCSharp
neural_net ( neural_net other ) : FANNCSharp
neural_net ( string configuration_file ) : FANNCSharp
print_connections ( ) : void
print_error ( ) : void
print_parameters ( ) : void
randomize_weights ( double min_weight, double max_weight ) : void
reset_MSE ( ) : void
reset_errno ( ) : void
reset_errstr ( ) : void
run ( double input ) : SWIGTYPE_p_double
save ( string configuration_file ) : bool
save_to_fixed ( string configuration_file ) : int
scale_input ( SWIGTYPE_p_double input_vector ) : void
scale_output ( SWIGTYPE_p_double output_vector ) : void
scale_train ( training_data data ) : void
set_activation_function ( ActivationFunction activation_function, int layer, int neuron ) : void
set_activation_function_hidden ( ActivationFunction activation_function ) : void
set_activation_function_layer ( ActivationFunction activation_function, int layer ) : void
set_activation_function_output ( ActivationFunction activation_function ) : void
set_activation_steepness ( double steepness, int layer, int neuron ) : void
set_activation_steepness_hidden ( double steepness ) : void
set_activation_steepness_layer ( double steepness, int layer ) : void
set_activation_steepness_output ( double steepness ) : void
set_bit_fail_limit ( double bit_fail_limit ) : void
set_callback ( global callback, global user_data ) : void
set_cascade_activation_functions ( SWIGTYPE_p_FANN__activation_function_enum cascade_activation_functions, uint cascade_activation_functions_count ) : void
set_cascade_activation_steepnesses ( double cascade_activation_steepnesses, uint cascade_activation_steepnesses_count ) : void
set_cascade_candidate_change_fraction ( float cascade_candidate_change_fraction ) : void
set_cascade_candidate_limit ( double cascade_candidate_limit ) : void
set_cascade_candidate_stagnation_epochs ( uint cascade_candidate_stagnation_epochs ) : void
set_cascade_max_cand_epochs ( uint cascade_max_cand_epochs ) : void
set_cascade_max_out_epochs ( uint cascade_max_out_epochs ) : void
set_cascade_num_candidate_groups ( uint cascade_num_candidate_groups ) : void
set_cascade_output_change_fraction ( float cascade_output_change_fraction ) : void
set_cascade_output_stagnation_epochs ( uint cascade_output_stagnation_epochs ) : void
set_cascade_weight_multiplier ( double cascade_weight_multiplier ) : void
set_error_log ( SWIGTYPE_p_FILE log_file ) : void
set_input_scaling_params ( training_data data, float new_input_min, float new_input_max ) : bool
set_learning_momentum ( float learning_momentum ) : void
set_learning_rate ( float learning_rate ) : void
set_output_scaling_params ( training_data data, float new_output_min, float new_output_max ) : bool
set_quickprop_decay ( float quickprop_decay ) : void
set_quickprop_mu ( float quickprop_mu ) : void
set_rprop_decrease_factor ( float rprop_decrease_factor ) : void
set_rprop_delta_max ( float rprop_delta_max ) : void
set_rprop_delta_min ( float rprop_delta_min ) : void
set_rprop_delta_zero ( float rprop_delta_zero ) : void
set_rprop_increase_factor ( float rprop_increase_factor ) : void
set_sarprop_step_error_shift ( float sarprop_step_error_shift ) : void
set_sarprop_step_error_threshold_factor ( float sarprop_step_error_threshold_factor ) : void
set_sarprop_temperature ( float sarprop_temperature ) : void
set_sarprop_weight_decay_shift ( float sarprop_weight_decay_shift ) : void
set_scaling_params ( training_data data, float new_input_min, float new_input_max, float new_output_min, float new_output_max ) : bool
set_train_error_function ( ErrorFunction train_error_function ) : void
set_train_stop_function ( StopFunction train_stop_function ) : void
set_training_algorithm ( TrainingAlgorithm training_algorithm ) : void
set_weight ( uint from_neuron, uint to_neuron, double weight ) : void
set_weight_array ( Connection connections, uint num_connections ) : void
test ( double input, double desired_output ) : SWIGTYPE_p_double
test_data ( training_data data ) : float
to_fann ( ) : SWIGTYPE_p_fann
train ( double input, double desired_output ) : void
train_epoch ( training_data data ) : float
train_on_data ( training_data data, uint max_epochs, uint epochs_between_reports, float desired_error ) : void
train_on_file ( string filename, uint max_epochs, uint epochs_between_reports, float desired_error ) : void

Private Methods

Method	Description
getCPtr ( neural_net obj ) : global::System.Runtime.InteropServices.HandleRef
neural_net ( global cPtr, bool cMemoryOwn ) : FANNCSharp

Method Details

Dispose() public method

public Dispose ( ) : void
return	void

cascadetrain_on_data() public method

public cascadetrain_on_data ( training_data data, uint max_neurons, uint neurons_between_reports, float desired_error ) : void
data	training_data
max_neurons	uint
neurons_between_reports	uint
desired_error	float
return	void

cascadetrain_on_file() public method

public cascadetrain_on_file ( string filename, uint max_neurons, uint neurons_between_reports, float desired_error ) : void
filename	string
max_neurons	uint
neurons_between_reports	uint
desired_error	float
return	void

clear_scaling_params() public method

public clear_scaling_params ( ) : bool
return	bool

copy_from_struct_fann() public method

public copy_from_struct_fann ( SWIGTYPE_p_fann other ) : void
other	FANNCSharp.SWIGTYPE_p_fann
return	void

create_from_file() public method

public create_from_file ( string configuration_file ) : bool
configuration_file	string
return	bool

create_shortcut() public method

public create_shortcut ( uint num_layers ) : bool
num_layers	uint
return	bool

create_shortcut_array() public method

public create_shortcut_array ( uint num_layers, SWIGTYPE_p_unsigned_int layers ) : bool
num_layers	uint
layers	FANNCSharp.SWIGTYPE_p_unsigned_int
return	bool

create_sparse() public method

public create_sparse ( float connection_rate, uint num_layers ) : bool
connection_rate	float
num_layers	uint
return	bool

create_sparse_array() public method

public create_sparse_array ( float connection_rate, uint num_layers, SWIGTYPE_p_unsigned_int layers ) : bool
connection_rate	float
num_layers	uint
layers	FANNCSharp.SWIGTYPE_p_unsigned_int
return	bool

create_standard() public method

public create_standard ( uint num_layers ) : bool
num_layers	uint
return	bool

create_standard_array() public method

public create_standard_array ( uint num_layers, SWIGTYPE_p_unsigned_int layers ) : bool
num_layers	uint
layers	FANNCSharp.SWIGTYPE_p_unsigned_int
return	bool

descale_input_() public method

public descale_input_ ( double descale_vector ) : void
descale_vector	double
return	void

descale_output_() public method

public descale_output_ ( double descale_vector ) : void
descale_vector	double
return	void

descale_train() public method

public descale_train ( training_data data ) : void
data	training_data
return	void

destroy() public method

public destroy ( ) : void
return	void

disable_seed_rand() public method

public disable_seed_rand ( ) : void
return	void

enable_seed_rand() public method

public enable_seed_rand ( ) : void
return	void

get_MSE() public method

public get_MSE ( ) : float
return	float

get_activation_function() public method

public get_activation_function ( int layer, int neuron ) : ActivationFunction
layer	int
neuron	int
return	ActivationFunction

get_activation_steepness() public method

public get_activation_steepness ( int layer, int neuron ) : double
layer	int
neuron	int
return	double

get_bias_array() public method

public get_bias_array ( SWIGTYPE_p_unsigned_int bias ) : void
bias	FANNCSharp.SWIGTYPE_p_unsigned_int
return	void

get_bit_fail() public method

public get_bit_fail ( ) : uint
return	uint

get_bit_fail_limit() public method

public get_bit_fail_limit ( ) : double
return	double

get_cascade_activation_functions() public method

public get_cascade_activation_functions ( ) : SWIGTYPE_p_FANN__activation_function_enum
return	FANNCSharp.SWIGTYPE_p_FANN__activation_function_enum

get_cascade_activation_functions_count() public method

public get_cascade_activation_functions_count ( ) : uint
return	uint

get_cascade_activation_steepnesses() public method

public get_cascade_activation_steepnesses ( ) : SWIGTYPE_p_double
return	SWIGTYPE_p_double

get_cascade_activation_steepnesses_count() public method

public get_cascade_activation_steepnesses_count ( ) : uint
return	uint

get_cascade_candidate_change_fraction() public method

public get_cascade_candidate_change_fraction ( ) : float
return	float

get_cascade_candidate_limit() public method

public get_cascade_candidate_limit ( ) : double
return	double

get_cascade_candidate_stagnation_epochs() public method

public get_cascade_candidate_stagnation_epochs ( ) : uint
return	uint

get_cascade_max_cand_epochs() public method

public get_cascade_max_cand_epochs ( ) : uint
return	uint

get_cascade_max_out_epochs() public method

public get_cascade_max_out_epochs ( ) : uint
return	uint

get_cascade_num_candidate_groups() public method

public get_cascade_num_candidate_groups ( ) : uint
return	uint

get_cascade_num_candidates() public method

public get_cascade_num_candidates ( ) : uint
return	uint

get_cascade_output_change_fraction() public method

public get_cascade_output_change_fraction ( ) : float
return	float

get_cascade_output_stagnation_epochs() public method

public get_cascade_output_stagnation_epochs ( ) : uint
return	uint

get_cascade_weight_multiplier() public method

public get_cascade_weight_multiplier ( ) : double
return	double

get_connection_array() public method

public get_connection_array ( Connection connections ) : void
connections	Connection
return	void

get_connection_rate() public method

public get_connection_rate ( ) : float
return	float

get_errno() public method

public get_errno ( ) : uint
return	uint

get_errstr() public method

public get_errstr ( ) : string
return	string

get_layer_array() public method

public get_layer_array ( SWIGTYPE_p_unsigned_int layers ) : void
layers	FANNCSharp.SWIGTYPE_p_unsigned_int
return	void

get_learning_momentum() public method

public get_learning_momentum ( ) : float
return	float

get_learning_rate() public method

public get_learning_rate ( ) : float
return	float

get_network_type() public method

public get_network_type ( ) : NetworkType
return	NetworkType

get_num_input() public method

public get_num_input ( ) : uint
return	uint

get_num_layers() public method

public get_num_layers ( ) : uint
return	uint

get_num_output() public method

public get_num_output ( ) : uint
return	uint

get_quickprop_decay() public method

public get_quickprop_decay ( ) : float
return	float

get_quickprop_mu() public method

public get_quickprop_mu ( ) : float
return	float

get_rprop_decrease_factor() public method

public get_rprop_decrease_factor ( ) : float
return	float

get_rprop_delta_max() public method

public get_rprop_delta_max ( ) : float
return	float

get_rprop_delta_min() public method

public get_rprop_delta_min ( ) : float
return	float

get_rprop_delta_zero() public method

public get_rprop_delta_zero ( ) : float
return	float

get_rprop_increase_factor() public method

public get_rprop_increase_factor ( ) : float
return	float

get_sarprop_step_error_shift() public method

public get_sarprop_step_error_shift ( ) : float
return	float

get_sarprop_step_error_threshold_factor() public method

public get_sarprop_step_error_threshold_factor ( ) : float
return	float

get_sarprop_temperature() public method

public get_sarprop_temperature ( ) : float
return	float

get_sarprop_weight_decay_shift() public method

public get_sarprop_weight_decay_shift ( ) : float
return	float

get_total_connections() public method

public get_total_connections ( ) : uint
return	uint

get_total_neurons() public method

public get_total_neurons ( ) : uint
return	uint

get_train_error_function() public method

public get_train_error_function ( ) : ErrorFunction
return	ErrorFunction

get_train_stop_function() public method

public get_train_stop_function ( ) : StopFunction
return	StopFunction

get_training_algorithm() public method

public get_training_algorithm ( ) : TrainingAlgorithm
return	TrainingAlgorithm

init_weights() public method

public init_weights ( training_data data ) : void
data	training_data
return	void

neural_net() public method

public neural_net ( ) : FANNCSharp
return	FANNCSharp

neural_net() public method

public neural_net ( NetworkType net_type, uint num_layers ) : FANNCSharp
net_type	NetworkType
num_layers	uint
return	FANNCSharp

neural_net() public method

public neural_net ( NetworkType net_type, uint num_layers, SWIGTYPE_p_unsigned_int layers ) : FANNCSharp
net_type	NetworkType
num_layers	uint
layers	FANNCSharp.SWIGTYPE_p_unsigned_int
return	FANNCSharp

neural_net() public method

public neural_net ( SWIGTYPE_p_fann other ) : FANNCSharp
other	FANNCSharp.SWIGTYPE_p_fann
return	FANNCSharp

neural_net() public method

public neural_net ( float connection_rate, uint num_layers ) : FANNCSharp
connection_rate	float
num_layers	uint
return	FANNCSharp

neural_net() public method

public neural_net ( float connection_rate, uint num_layers, SWIGTYPE_p_unsigned_int layers ) : FANNCSharp
connection_rate	float
num_layers	uint
layers	FANNCSharp.SWIGTYPE_p_unsigned_int
return	FANNCSharp

neural_net() public method

public neural_net ( neural_net other ) : FANNCSharp
other	neural_net
return	FANNCSharp

neural_net() public method

public neural_net ( string configuration_file ) : FANNCSharp
configuration_file	string
return	FANNCSharp

print_connections() public method

public print_connections ( ) : void
return	void

print_error() public method

public print_error ( ) : void
return	void

print_parameters() public method

public print_parameters ( ) : void
return	void

randomize_weights() public method

public randomize_weights ( double min_weight, double max_weight ) : void
min_weight	double
max_weight	double
return	void

reset_MSE() public method

public reset_MSE ( ) : void
return	void

reset_errno() public method

public reset_errno ( ) : void
return	void

reset_errstr() public method

public reset_errstr ( ) : void
return	void

run() public method

public run ( double input ) : SWIGTYPE_p_double
input	double
return	SWIGTYPE_p_double

save() public method

public save ( string configuration_file ) : bool
configuration_file	string
return	bool

save_to_fixed() public method

public save_to_fixed ( string configuration_file ) : int
configuration_file	string
return	int

scale_input() public method

public scale_input ( SWIGTYPE_p_double input_vector ) : void
input_vector	SWIGTYPE_p_double
return	void

scale_output() public method

public scale_output ( SWIGTYPE_p_double output_vector ) : void
output_vector	SWIGTYPE_p_double
return	void

scale_train() public method

public scale_train ( training_data data ) : void
data	training_data
return	void

set_activation_function() public method

public set_activation_function ( ActivationFunction activation_function, int layer, int neuron ) : void
activation_function	ActivationFunction
layer	int
neuron	int
return	void

set_activation_function_hidden() public method

public set_activation_function_hidden ( ActivationFunction activation_function ) : void
activation_function	ActivationFunction
return	void

set_activation_function_layer() public method

public set_activation_function_layer ( ActivationFunction activation_function, int layer ) : void
activation_function	ActivationFunction
layer	int
return	void

set_activation_function_output() public method

public set_activation_function_output ( ActivationFunction activation_function ) : void
activation_function	ActivationFunction
return	void

set_activation_steepness() public method

public set_activation_steepness ( double steepness, int layer, int neuron ) : void
steepness	double
layer	int
neuron	int
return	void

set_activation_steepness_hidden() public method

public set_activation_steepness_hidden ( double steepness ) : void
steepness	double
return	void

set_activation_steepness_layer() public method

public set_activation_steepness_layer ( double steepness, int layer ) : void
steepness	double
layer	int
return	void

set_activation_steepness_output() public method

public set_activation_steepness_output ( double steepness ) : void
steepness	double
return	void

set_bit_fail_limit() public method

public set_bit_fail_limit ( double bit_fail_limit ) : void
bit_fail_limit	double
return	void

set_callback() public method

public set_callback ( global callback, global user_data ) : void
callback	global
user_data	global
return	void

set_cascade_activation_functions() public method

public set_cascade_activation_functions ( SWIGTYPE_p_FANN__activation_function_enum cascade_activation_functions, uint cascade_activation_functions_count ) : void
cascade_activation_functions	FANNCSharp.SWIGTYPE_p_FANN__activation_function_enum
cascade_activation_functions_count	uint
return	void

set_cascade_activation_steepnesses() public method

public set_cascade_activation_steepnesses ( double cascade_activation_steepnesses, uint cascade_activation_steepnesses_count ) : void
cascade_activation_steepnesses	double
cascade_activation_steepnesses_count	uint
return	void

set_cascade_candidate_change_fraction() public method

public set_cascade_candidate_change_fraction ( float cascade_candidate_change_fraction ) : void
cascade_candidate_change_fraction	float
return	void

set_cascade_candidate_limit() public method

public set_cascade_candidate_limit ( double cascade_candidate_limit ) : void
cascade_candidate_limit	double
return	void

set_cascade_candidate_stagnation_epochs() public method

public set_cascade_candidate_stagnation_epochs ( uint cascade_candidate_stagnation_epochs ) : void
cascade_candidate_stagnation_epochs	uint
return	void

set_cascade_max_cand_epochs() public method

public set_cascade_max_cand_epochs ( uint cascade_max_cand_epochs ) : void
cascade_max_cand_epochs	uint
return	void

set_cascade_max_out_epochs() public method

public set_cascade_max_out_epochs ( uint cascade_max_out_epochs ) : void
cascade_max_out_epochs	uint
return	void

set_cascade_num_candidate_groups() public method

public set_cascade_num_candidate_groups ( uint cascade_num_candidate_groups ) : void
cascade_num_candidate_groups	uint
return	void

set_cascade_output_change_fraction() public method

public set_cascade_output_change_fraction ( float cascade_output_change_fraction ) : void
cascade_output_change_fraction	float
return	void

set_cascade_output_stagnation_epochs() public method

public set_cascade_output_stagnation_epochs ( uint cascade_output_stagnation_epochs ) : void
cascade_output_stagnation_epochs	uint
return	void

set_cascade_weight_multiplier() public method

public set_cascade_weight_multiplier ( double cascade_weight_multiplier ) : void
cascade_weight_multiplier	double
return	void

set_error_log() public method

public set_error_log ( SWIGTYPE_p_FILE log_file ) : void
log_file	FANNCSharp.SWIGTYPE_p_FILE
return	void

set_input_scaling_params() public method

public set_input_scaling_params ( training_data data, float new_input_min, float new_input_max ) : bool
data	training_data
new_input_min	float
new_input_max	float
return	bool

set_learning_momentum() public method

public set_learning_momentum ( float learning_momentum ) : void
learning_momentum	float
return	void

set_learning_rate() public method

public set_learning_rate ( float learning_rate ) : void
learning_rate	float
return	void

set_output_scaling_params() public method

public set_output_scaling_params ( training_data data, float new_output_min, float new_output_max ) : bool
data	training_data
new_output_min	float
new_output_max	float
return	bool

set_quickprop_decay() public method

public set_quickprop_decay ( float quickprop_decay ) : void
quickprop_decay	float
return	void

set_quickprop_mu() public method

public set_quickprop_mu ( float quickprop_mu ) : void
quickprop_mu	float
return	void

set_rprop_decrease_factor() public method

public set_rprop_decrease_factor ( float rprop_decrease_factor ) : void
rprop_decrease_factor	float
return	void

set_rprop_delta_max() public method

public set_rprop_delta_max ( float rprop_delta_max ) : void
rprop_delta_max	float
return	void

set_rprop_delta_min() public method

public set_rprop_delta_min ( float rprop_delta_min ) : void
rprop_delta_min	float
return	void

set_rprop_delta_zero() public method

public set_rprop_delta_zero ( float rprop_delta_zero ) : void
rprop_delta_zero	float
return	void

set_rprop_increase_factor() public method

public set_rprop_increase_factor ( float rprop_increase_factor ) : void
rprop_increase_factor	float
return	void

set_sarprop_step_error_shift() public method

public set_sarprop_step_error_shift ( float sarprop_step_error_shift ) : void
sarprop_step_error_shift	float
return	void

set_sarprop_step_error_threshold_factor() public method

public set_sarprop_step_error_threshold_factor ( float sarprop_step_error_threshold_factor ) : void
sarprop_step_error_threshold_factor	float
return	void

set_sarprop_temperature() public method

public set_sarprop_temperature ( float sarprop_temperature ) : void
sarprop_temperature	float
return	void

set_sarprop_weight_decay_shift() public method

public set_sarprop_weight_decay_shift ( float sarprop_weight_decay_shift ) : void
sarprop_weight_decay_shift	float
return	void

set_scaling_params() public method

public set_scaling_params ( training_data data, float new_input_min, float new_input_max, float new_output_min, float new_output_max ) : bool
data	training_data
new_input_min	float
new_input_max	float
new_output_min	float
new_output_max	float
return	bool

set_train_error_function() public method

public set_train_error_function ( ErrorFunction train_error_function ) : void
train_error_function	ErrorFunction
return	void

set_train_stop_function() public method

public set_train_stop_function ( StopFunction train_stop_function ) : void
train_stop_function	StopFunction
return	void

set_training_algorithm() public method

public set_training_algorithm ( TrainingAlgorithm training_algorithm ) : void
training_algorithm	TrainingAlgorithm
return	void

set_weight() public method

public set_weight ( uint from_neuron, uint to_neuron, double weight ) : void
from_neuron	uint
to_neuron	uint
weight	double
return	void

set_weight_array() public method

public set_weight_array ( Connection connections, uint num_connections ) : void
connections	Connection
num_connections	uint
return	void

test() public method

public test ( double input, double desired_output ) : SWIGTYPE_p_double
input	double
desired_output	double
return	SWIGTYPE_p_double

test_data() public method

public test_data ( training_data data ) : float
data	training_data
return	float

to_fann() public method

public to_fann ( ) : SWIGTYPE_p_fann
return	FANNCSharp.SWIGTYPE_p_fann

train() public method

public train ( double input, double desired_output ) : void
input	double
desired_output	double
return	void

train_epoch() public method

public train_epoch ( training_data data ) : float
data	training_data
return	float

train_on_data() public method

public train_on_data ( training_data data, uint max_epochs, uint epochs_between_reports, float desired_error ) : void
data	training_data
max_epochs	uint
epochs_between_reports	uint
desired_error	float
return	void

train_on_file() public method

public train_on_file ( string filename, uint max_epochs, uint epochs_between_reports, float desired_error ) : void
filename	string
max_epochs	uint
epochs_between_reports	uint
desired_error	float
return	void

Property Details

swigCMemOwn protected_oe property

protected bool swigCMemOwn
return	bool